Integrating urban analysis, generative design, and evolutionary optimization for solving urban design problems

Reinhard Koenig, Yufan Miao, Anna Aichinger, Katja Knecht and Kateryna Konieva
Additional contact information
Reinhard Koenig: Bauhaus-University Weimar, Germany; Austrian Institute of Technology (AIT), Austria; Singapore-ETH Centre, Singapore
Yufan Miao: Singapore-ETH Centre, Singapore
Anna Aichinger: Austrian Institute of Technology (AIT), Austria
Kateryna Konieva: Singapore-ETH Centre, Singapore

Environment and Planning B, 2020, vol. 47, issue 6, 997-1013

Abstract: To better support urban designers in planning sustainable, resilient, and livable urban environments, new methods and tools are needed. A variety of computational approaches have been proposed, including different forms of spatial analysis to evaluate the performance of design proposals, or the automated generation of urban design proposals based on specific parameters. However, most of these propositions have produced separate tools and disconnected workflows. In the context of urban design optimization procedures, one of the main challenges of integrating urban analytics and generative methods is a suitable computational representation of the urban design problem. To overcome this difficulty, we present a holistic data representation for urban fabrics, including the layout of street networks, parcels, and buildings, which can be used efficiently with evolutionary optimization algorithms. We demonstrate the use of the data structure implemented for the software Grasshopper for Rhino3D as part of a flexible, modular, and extensible optimization system that can be used for a variety of urban design problems and is able to reconcile potentially contradicting design goals in a semi-automated design process. The proposed optimization system aims to assist a designer by populating the design space with options for more detailed exploration. We demonstrate the functionality of our system using the example of an urban master-design project for the city of Weimar.

Keywords: Evolutionary multi-criteria optimization; generative design; spatial analysis; urban design (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/2399808319894986 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:47:y:2020:i:6:p:997-1013

DOI: 10.1177/2399808319894986

Access Statistics for this article

More articles in Environment and Planning B
Bibliographic data for series maintained by SAGE Publications ().